SCRAPE: Scalable randomness attested by public entities

Ignacio Cascudo, Bernardo David*

*Kontaktforfatter

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

60 Citationer (Scopus)

Abstract

Uniform randomness beacons whose output can be publicly attested to be unbiased are required in several cryptographic protocols. A common approach to building such beacons is having a number parties run a coin tossing protocol with guaranteed output delivery (so that adversaries cannot simply keep honest parties from obtaining randomness, consequently halting protocols that rely on it). However, current constructions face serious scalability issues due to high computational and communication overheads. We present a coin tossing protocol for an honest majority that allows for any entity to verify that an output was honestly generated by observing publicly available information (even after the execution is complete), while achieving both guaranteed output delivery and scalability. The main building block of our construction is the first Publicly Verifiable Secret Sharing scheme for threshold access structures that requires only O(n) exponentiations. Previous schemes required O(nt) exponentiations (where t is the threshold) from each of the parties involved, making them unfit for scalable distributed randomness generation, which requires t = n/2 and thus O(n2) exponentiations.

OriginalsprogEngelsk
TitelApplied Cryptography and Network Security : 15th International Conference, ACNS 2017, Proceedings
Antal sider20
ForlagSpringer
Publikationsdato2017
Sider537-556
ISBN (Trykt)978-3-319-61203-4
ISBN (Elektronisk)978-3-319-61204-1
DOI
StatusUdgivet - 2017
Begivenhed15th International Conference on Applied Cryptography and Network Security, ACNS 2017 - Kanazawa, Japan
Varighed: 10 jul. 201712 jul. 2017

Konference

Konference15th International Conference on Applied Cryptography and Network Security, ACNS 2017
Land/OmrådeJapan
ByKanazawa
Periode10/07/201712/07/2017
NavnLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Vol/bind10355 LNCS
ISSN0302-9743

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